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-rw-r--r--tests/use_case/asr/InferenceTestWav2Letter.cc39
1 files changed, 19 insertions, 20 deletions
diff --git a/tests/use_case/asr/InferenceTestWav2Letter.cc b/tests/use_case/asr/InferenceTestWav2Letter.cc
index e6012c3..991617c 100644
--- a/tests/use_case/asr/InferenceTestWav2Letter.cc
+++ b/tests/use_case/asr/InferenceTestWav2Letter.cc
@@ -1,6 +1,6 @@
/*
- * SPDX-FileCopyrightText: Copyright 2021 Arm Limited and/or its affiliates <open-source-office@arm.com>
- * SPDX-License-Identifier: Apache-2.0
+ * SPDX-FileCopyrightText: Copyright 2021 Arm Limited and/or its affiliates
+ * <open-source-office@arm.com> SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
@@ -14,10 +14,10 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
+#include "BufAttributes.hpp"
#include "TensorFlowLiteMicro.hpp"
-#include "Wav2LetterModel.hpp"
#include "TestData_asr.hpp"
-#include "BufAttributes.hpp"
+#include "Wav2LetterModel.hpp"
#include <catch.hpp>
#include <random>
@@ -51,11 +51,9 @@ bool RunInferenceRandom(arm::app::Model& model)
std::random_device rndDevice;
std::mt19937 mersenneGen{rndDevice()};
- std::uniform_int_distribution<short> dist {-128, 127};
+ std::uniform_int_distribution<short> dist{-128, 127};
- auto gen = [&dist, &mersenneGen](){
- return dist(mersenneGen);
- };
+ auto gen = [&dist, &mersenneGen]() { return dist(mersenneGen); };
std::vector<int8_t> randomAudio(inputTensor->bytes);
std::generate(std::begin(randomAudio), std::end(randomAudio), gen);
@@ -64,21 +62,22 @@ bool RunInferenceRandom(arm::app::Model& model)
return true;
}
-TEST_CASE("Running random inference with TensorFlow Lite Micro and Wav2LetterModel Int8", "[Wav2Letter]")
+TEST_CASE("Running random inference with TensorFlow Lite Micro and Wav2LetterModel Int8",
+ "[Wav2Letter]")
{
arm::app::Wav2LetterModel model{};
REQUIRE_FALSE(model.IsInited());
REQUIRE(model.Init(arm::app::tensorArena,
- sizeof(arm::app::tensorArena),
- arm::app::asr::GetModelPointer(),
- arm::app::asr::GetModelLen()));
+ sizeof(arm::app::tensorArena),
+ arm::app::asr::GetModelPointer(),
+ arm::app::asr::GetModelLen()));
REQUIRE(model.IsInited());
REQUIRE(RunInferenceRandom(model));
}
-template<typename T>
+template <typename T>
void TestInference(const T* input_goldenFV, const T* output_goldenFV, arm::app::Model& model)
{
TfLiteTensor* inputTensor = model.GetInputTensor(0);
@@ -101,9 +100,10 @@ void TestInference(const T* input_goldenFV, const T* output_goldenFV, arm::app::
TEST_CASE("Running inference with Tflu and Wav2LetterModel Int8", "[Wav2Letter]")
{
REQUIRE(NUMBER_OF_IFM_FILES == NUMBER_OF_IFM_FILES);
- for (uint32_t i = 0 ; i < NUMBER_OF_IFM_FILES; ++i) {
- auto input_goldenFV = get_ifm_data_array(i);;
- auto output_goldenFV = get_ofm_data_array(i);
+ for (uint32_t i = 0; i < NUMBER_OF_IFM_FILES; ++i) {
+ auto input_goldenFV = GetIfmDataArray(i);
+ ;
+ auto output_goldenFV = GetOfmDataArray(i);
DYNAMIC_SECTION("Executing inference with re-init")
{
@@ -111,13 +111,12 @@ TEST_CASE("Running inference with Tflu and Wav2LetterModel Int8", "[Wav2Letter]"
REQUIRE_FALSE(model.IsInited());
REQUIRE(model.Init(arm::app::tensorArena,
- sizeof(arm::app::tensorArena),
- arm::app::asr::GetModelPointer(),
- arm::app::asr::GetModelLen()));
+ sizeof(arm::app::tensorArena),
+ arm::app::asr::GetModelPointer(),
+ arm::app::asr::GetModelLen()));
REQUIRE(model.IsInited());
TestInference<int8_t>(input_goldenFV, output_goldenFV, model);
-
}
}
}